Neural prosthesis system and method of control

ABSTRACT

Multiple designs, systems, methods and processes for control using electrical signals recorded from clinically paralyzed muscles and nerves are presented. The discomplete neural prosthesis system and method for clinically paralyzed humans utilizes a controller. The controller is adapted to receive a volitional electrical signal generated by the human that is manifest below the lesion that causes the clinical paralysis. The controller uses at least the volitional electrical signal to generate a control signal that is output back to a plant to change the state of the plant, which in one aspect is one or more of the user&#39;s paralyzed muscles to achieve a functional result or to devices in the environment around the user that are adapted to receive commands from the controller.

CROSS-REFERENCE TO RELATED APPLICATIONS

This application claims the benefit of U.S. Application No. 61/024,789filed 30 Jan. 2008.

This work was support at least in part by the National Institutes ofHealth (NIH) under NIH grant number T32-EB04314. Accordingly, the UnitedStates government may have certain rights herein. This work wassupported at least in part by the State of Ohio Biomedical ResearchCommercialization Program, Ohio Neurostimulation and NeuromodulationPartnership program.

TECHNICAL FIELD

The subject matter described herein relates to systems, and methods forcontrol using electrical signals obtained from muscles and nerves thatare clinically paralyzed.

BACKGROUND

Neurological trauma, dysfunction or disease can leave persons withsevere and life threatening motor or sensory disabilities that cancompromise the ability to control basic vital functions. Persons withneurological impairments often rely on personal assistants, adaptiveequipment and environmental modifications to facilitate their dailyactivities. Neural prostheses are highly effective methods for restoringfunction to individuals with neurological deficits by electricallymanipulating the peripheral or central nervous systems. By passing smallelectrical currents through a nerve or directly to the motor units of amuscle via intramuscular, epimysial, and surface electrodes, neuralprostheses can initiate action potentials which in turn trigger therelease of chemical neurotransmitters to affect an end organ, such as amuscle. Techniques exist to selectively activate axons of any size orlocation within a nerve or fascicle, making it possible topreferentially target small sensory fibers or duplicate neutral motorunit recruitment in order to minimize fatigue and grade the strength ofa stimulated muscular contraction. In addition to exciting the nervoussystem, the proper current waveform and configuration of electrodes canblock nerve conduction and inhibit action potential transmission. Thus,in principle any end organ normally under neural control is a candidatefor neural prosthetic control.

Neural prostheses may consist of wholly external components with onlylimited surface or percutaneous electrical contacts, combinations ofboth external and implanted components or in some cases fully implantedsystems with limited or no interface to components external to the body.In some cases, recording components of neural prostheses may interfacewith external systems that impact the user such as external mechanicalorthotics or other devices. In further advances in the field of neuralprosthesis, networked systems are developed whereby combinations ofsensors and actuators are implanted within the user and networked into acommon system. Some exemplary systems are described for example in U.S.Pat. No. 5,167,229 to Peckham, et. al., and U.S. Pat. No. 7,260,436 toKilgore et. al.

Neural prostheses commonly operate in one of two separate control modes,open loop and closed loop. In the case of open loop control, the neuralprostheses applies electrical signals to the body based on a pre-definedsimulation pattern that does not change after initiation based en themovement or change of body state. The pre-defined stimulation pattern istriggered using a variety of inputs, including joysticks, voicecommands, or feedback from other sensors that provide information aboutthe current state or orientation of the body and the user's desiredstate. Closed loop control modes use information about the state of theuser's body during stimulation to further resolve and tune thestimulation to achieve more accurate and precise motion. In order toimplement these various control modes, it is common for neuralprostheses to use sensors to allow the user to issue command signals tothe system and for estimating the body state, i.e. its position,orientation, force etc.

Existing neural prostheses utilize two different types of commandsignals, a logical or trigger command signal and a continuous orgraduated control signal. The logical control signals are used to turnexternal devices on or off, initiate a predefined motion or stimulationpattern, or cycle through a set of different patterns such as differentgrasp patterns such as lateral and palmer grasp in the case of an upperextremity neural prosthesis, and lock or unlock a device at variousforce levels. Examples of logical command signals include push buttonswitches, reaching a specific threshold value with a command signalrecorded from a part of the body, or holding a command signal at acertain threshold level for a predetermined length of time. A continuouscommand signal is required to control degree of motion or position andforce applied by the neural prosthesis. Some examples of command signalsources include joint positions or potentiometer readings obtained fromjoints where the user retains volitional control, myoelectric signalsobtained from muscles above the lesion where the user maintainsfunctional control such as voluntary control over wrist extensor musclesby a tetraplegic user with a C6 level injury. The goal in the design ofneural prostheses is to create command inputs that are a naturalextension of the user's intact motor system.

It is clear that neural prosthetic approaches can provide boththerapeutic and functional benefits to individuals with impairments dueto neurological injury or disorder. However, a significant disadvantageof prior neural prostheses is due to a lack natural command signals thatare easy for a user to internalize and use to command the neuralprosthesis.

There is increasing evidence that even in cases of severe spinal traumathat result in clinically complete Spinal Cord Injuries (SCI) some axonsremain intact across the lesion. Traditional techniques for assessingSCI involve manual muscle testing and sensory testing. These traditionaltechniques have a functional basis for evaluating whether or notvolitional control exists; meaning volitional control below the lesionis measured by evaluating the force manifest by the muscle undervolitional control of the injured subject. Thus an SCI is determined tobe functionally or clinically complete based on the presence or absenceof visible or palpable movement in the muscles below the lesion. Inrecent studies seeking to develop new diagnostic techniques to analyzelesions in clinically complete SCI it has been found that there existssufficient numbers of axons that cross the lesion that allow volitionalelectrical signals that cross the lesion and be manifest below thelesion, even though the signals are not strong enough to cause visiblemuscle contraction. For example, the volitional electrical signal mayincomplete innervate a muscle and thus not have the ability to triggerenough motor units to cause a physically manifest contraction of themuscle. However, this sub-functional activation of motor units withinthe muscle does result in a measurable electromyography (EMG) signals.Someone with an SCI injury or other injury or trauma to the nervoussystem that is functionally or clinically complete, with no clinicallymanifest movement of muscles below the lesion, but who upon closeranalysis is found to still generate volitional electrical potentials inmuscles and nerves below the lesion is referred to herein using the termdiscomplete neural lesion.

SUMMARY OF INVENTION

In one embodiment the present system and method provides a discompleteneural controller for a human with a discomplete neural lesion ordiscomplete SCI, referred to generally as a discomplete lesion, thataccepts a volitional electrical potential generated by the human belowthe discomplete lesion. The volitional electrical potential is used bythe system and method to generate a control signal, where the controlsignal is a function of the volitional electrical potential. Thatcontrol signal is in turn applied to a plant. In another aspect, thevolitional electrical potential is collected via an electrode. In stillother aspects, the volitional electrical potential is measured andquantified by the controller and the measurement is used to modulate thecontrol signal output to the plant.

In another embodiment the present system and method provides adiscomplete neural prosthesis for a human with a discomplete neurallesion or discomplete SCI, referred to generally as a discompletelesion, that accepts a volitional electrical potential generated by thehuman below the discomplete, lesion. The volitional electrical potentialis used by the system and method to generate a control signal, where thecontrol signal is a function of the volitional electrical potential.That control signal is in turn applied to a plant that comprises atleast in part human muscle. In at aspect, the volitional electricalpotential is collected via an electrode. It still other aspects, thevolitional electrical potential is measured and quantified by thecontroller and the measurement is used to modulate the control signaloutput to the plant. In another aspect the control signal is applied toclinically paralyzed human muscle. In yet another aspect the plantfurther comprises a device in the environment.

BRIEF DESCRIPTION OF THE DRAWINGS

The accompanying figures depict multiple embodiments of a system andmethod for control using electrical signals recorded from muscles andnerves that are clinically paralyzed. A brief description of each figureis provided below. Elements with the same reference numbers in eachfigure indicate identical or functionally similar elements.Additionally, the left-most digit(s) of a reference number identifiesthe drawings in which the reference number first appears.

FIG. 1 is a block diagram of the system and method for recording andacting based on electrical signals recorded from a clinically paralyzedmuscle.

FIG. 2 is an example of an embodiment of the system and method appliedto an upper arm.

FIG. 3 is a block diagram of a signal processing circuit for samplingvolitional electrical potential in the presence of stimulationartifacts.

FIG. 4 is a functional illustration of a partially implanted system forcontrolling upper extremity motion via electrical signals recorded fromclinically paralyzed muscles.

FIG. 5 is a functional illustration of an external system forcontrolling lower extremity motion via electrical signals recorded fromclinically paralyzed muscles.

FIG. 6 is a plot showing experimental results of a human with aclinically complete lesion that demonstrates the ability of the user togenerate a volitional electrical potential below the lesion.

The present invention in described at least in part with reference toblock diagrams and operational flow charts. It is to be understood thatthe functions/acts noted in the blocks may occur out of the order notedin the operational illustrations. For example, two blocks shown insuccession may in fact be executed substantially concurrently or theblocks may sometimes be executed in the reverse order, depending uponthe functionality/acts involved, including for example executing asasynchronous threads on a processor. Although some of the diagramsinclude arrows on communication paths to show a primary direction ofcommunication, it is to be understood that communication may occur inthe opposite direction to the depicted arrows.

DETAILED DESCRIPTION

Multiple embodiments of a system and method utilizing electrical signalsobtained from clinically paralyzed muscle or nerve as a control inputare presented herein. Those of ordinary skill in the art can readily usethis disclosure to create alternative embodiments using the teachingcontained herein.

Lexicon

The following terms used herein have the meanings as follows.

As used herein, the term “discomplete lesion” or “discomplete paralysis”means an injury or damage to the neural pathway between the muscle tothe brain, such as that typified by a Spinal Cord Injury (SCI) or thosethat arise from a variety of diseases such as amyotrophic lateralsclerosis (ALS) or demyelinating diseases that result in functionally orclinically complete (i.e. no externally observable, volitional, physicalmotor function below the lesion) paralysis of one or more muscles belowthe lesion. For example, in the case of a discomplete lesion causes byan SCI, there may exist at least some neural tissue (i.e. axons) at thelesion thereby allowing subclinical manifestation of some,non-clinically observable volitional control below the lesion. In oneexample, a discomplete SCI results in a person being unable to cause amuscle innervated below the lesion to contract in a physicallyobservable manner, however, since it is a discomplete lesion, sufficientvolitional control exists to cause measurable myoelectric signals ormeasurable signals within the peripheral nerves, such measurable signalsmanifest below the lesion and controlled by the person with thediscomplete lesion are referred to as volitional electrical potentials.

As used herein, the term “electrode” means an operable connection to amuscle or nerve that allows an electrical potential to be recorded orapplied. An electrode can be further described by its location—i.e.internal, external or percutaneous; electrical or other recordingcharacteristics—i.e. unipolar, bipolar, laplacian, magnetic or optical;and with respect to internal electrodes by its placement i.e.intramuscular, epimysial or nerve.

As used herein, when the term “function” is used to describe arelationship between one variable or parameter and a second variable orparameter, the relationship so described is not considered to be anexclusive relationship unless expressly stated, rather the othervariables or parameters that are not mentioned or described but that areknown to those of ordinarily still in the art may also have a functionalrelationship to the second variable or parameter. By way of example, ifx is described as a function of y the statement is not intended to limitx's value to only being described by y unless expressly stated, ratherthe variable x may also be a function of other variables (e.g.x=f(y,t′).

As used herein the term “computer component” refers to a computer andelements of a computer, such as hardware, firmware, software, acombination thereof, or software in execution. For example, a computercomponent can include by way of example, a process running on aprocessor, a processor, an object, an executable, an execution thread, aprogram, and a computer itself. One or more computer components can invarious embodiments reside on a server and the server can be comprisedof multiple computer components. One or more computer components are insome cases referred to as computer systems whereby one or more computercomponents operate together to achieve some functionality. One or morecomputer components can reside within a process or thread of executionand a computer component can be localized on one computer or distributedbetween two or more computers.

An “operable connection” is one in which signals or actual communicationflow at logical communication flow may be sent or received. Usually, anoperable connection includes a physical interface, an electricalinterface, or a data interface, but it is to be noted that an operableconnection may consist of differing combinations of these or other typesof connections sufficient to allow operable control.

As used herein, the term “signal” may take the form of a continuouswaveform or discrete value(s), such as electrical potentials, electricalcurrents, magnetic fields, optical fields, or digital value(s) in amemory or register, present in electrical, optical or other form.

The term “controller” as used herein indicates a method, process, orcomputer component adapted to affect a plant (i.e. the system to becontrolled or effected).

The term “state” as used herein refers to a set of variables that definethe characteristics of a particular system in a specific combination. Inone non-limiting example, the state of a single axis, hinged joint isexpressed as a vector comprised of the current angle, angular velocityand angular acceleration. In other aspects the state of a systemincludes otherwise unmeasureable or practically unobservable values.

To the extent that the term “includes” is employed in the detaileddescription or the claims, it is intended to be inclusive manner similarto the term “comprising,” as that term is interpreted when employed as atransitional word in a claim.

To the extent that the term “or” is employed in the claims (e.g., A orB) it is intended to mean “A or B or both”. When the author intends toindicate “only A or B but not both”, then the author will employ theterm “A or B but not both”. Thus, use of the term “or” in the claims isthe inclusive, and not the exclusive, use.

System and Method of Control

The present system and method is typified in the block diagram shown inFIG. 1. A discomplete neural controller 100 receives at least in part acommand signal from a volitional electrical potential measured below anSCI lesion, referred to as a volitional electrical potential 102. Thevolitional electrical potential 102 is manifest as electrical potentialcreated in peripheral nerves below the lesion or as myoelectric signalswithin a muscle that is innervated below the lesion, which in eithercase do not otherwise manifest as clinically meaningful motion of themuscle.

The volitional electrical potential 102 is received by a controller 104via an operable connection to an electrode adapted to measure thevolitional electrical potential 102. As known to those of ordinary skillin the art typically an electrode is applied to either the muscle or thenerve or in the vicinity of either of the foregoing. The electrode isused to probe the volitional electrical potential 102 present in eitherthe nerve or the muscle. In one embodiment the electrode is directlyconnected to the controller 104 and the controller 104 possesses a meansfor measuring the electrical potential. In one embodiment, thecontroller 104 means for measuring the volitional electrical potential102 includes a high impedance input amplifier. In other embodiments thecontroller 104 means for measuring the volitional electrical potential102 further comprises analog or digital filters that are adapted toattenuate electrical potential not associated with the volitionalelectrical potential 102. In still another embodiment the controller 104means for measuring the volitional electrical potential 102 furthercomprises an analog to digital (A/D) converter for converting an analogmeasurement of the volitional electrical potential 102 to a digitalrepresentation suitable for processing by a digital computer component.In other alternative embodiments, the electrode is an active electrodewith either analog signal processing or analog signal processing and A/Dconversation incorporated into the body of the electrode itself. Inthese other alternative embodiments, the controller 104 is adapted toaccept the processed signal from the active electrode.

In yet another embodiment, a distributed sensor module as typified bythe sensor modules disclosed in U.S. Pat. No. 7,260,436 to Kilgore, et.al., is operably connected to the electrode to measure the volitionalelectrical potential 102. The distributed sensor module in one aspectincorporates analog signal processing and A/D conversion suitable toconvert the volitional electrical potential 102 to a digital signal. Thedigital signal is then useable by other sensor modules that whennetworked together enable a controller 104 to be distributed across oraround the user's body.

In still other embodiments measurement electrodes that do not rely upondirect conduction of electrical potential are used to detect thevolitional electrical potential 102. For example, in one non-limitingembodiment, an electrode that uses a magnetic field sensor estimates thevolitional electrical potential 102 manifest in the muscle or theperipheral nerve. In another example, an electrode comprising a fiberoptic sensor utilizes optical sensing to estimate volitional electricalpotential 102. In this case the controller 104 is adapted to accept theoptical signals generated in response to the volitional electricalpotential 102. As can be appreciated by those of ordinary skill in theart, the discomplete neural controller 100 is readily adapted to using avariety of different electrodes, regardless of the specific sensingmethod, (i.e. conductive, nonconductive, optical, magnetic etc.) used tomeasure the volitional electrical potential 102.

The controller 104 uses the measured volitional electrical potential 102as a command signal from the user indicative of the user's desiredaction. As can be appreciated by one of ordinary skill the commandsignal may comprise a simple binary, on/off command. The controller 104thus maps a baseline or quiescent volitional electrical potential 102 toan on or off state while the complimentary state is mapped to an activeor elevated volitional electrical potential 102. In other embodimentsthe command signal may comprise a graduated response where thecharacteristics of the volitional electrical potential 102, such astotal power, peak power, or frequently is used to create a graduatedcommand signal. In one embodiment, the total power of the volitionalelectrical signal 102 is mapped by the controller 104 onto a set of fivecommand states. In this manner the user is able to apply graduatedcommands to the controller 104. In other embodiments the command signalis a combination of one or more volitional electrical signal 102. Instill other embodiment the command signal is a combination of volitionalelectrical signals 102 in combination with other sensor inputs. In yetanother embodiment, a series of volitional electrical signals 102 thatare temporally related are used to create the command signal. In oneembodiment a series of volitional electrical signal 102 pulses within aspecific time frame are mapped to a specific command signal. Variouscommand signal generation embodiments are described in greater detailbelow.

Still referring to FIG. 1, the discomplete neural controller 100includes a control output 106 that is operably connected to thecontroller 104. The control output 106 accepts the command signalgenerated by the controller 104. The control output 106 is operablyconnected to the plant 108 and generates a control signal adapted to beapplied to the plant 108. The plant 108 in one embodiment, i.e. a neuralprosthesis embodiment is a muscle, below the lesion, that is otherwiseclinically paralyzed. In which case, the control signal generated by thecontrol output 106 is a series of charge balanced electrical pulsesadapted to be applied to the muscle via an electrode to cause the musclemotor units to contract thereby eliciting a functional motion of theotherwise paralyzed muscle. In another embodiment the plant 108comprises an external device such as an active orthosis or prostheticdevice that responds to the control output 106. In another embodiment,the plain 108 comprise an assistive or rehabilitative device in theenvironment, such as a home control, remote control, remote lightswitch, power wheel chairs, communication devices, or other devicesdesigned to remotely activate or otherwise assist the user withactivities of daily living. In another embodiment, the plant 108 is anydevice that is adapted to accept digital communication such as a homeautomation controller or computer system.

As used herein, the discomplete neural controller 100 refers generallyto a controller that is activated by a volitional electric potential 102that in turn interfaces with and applies a signal to any plant 108. Theplant 108 may comprise a single device or muscle or multiple devices ormuscles. If the plant 108 comprises at least one muscle, then thediscomplete neural controller 100 may be referred to as a neuralprosthesis with no lack of generality.

Fully Implanted System Discomplete Neural Prosthesis

Referring now to FIG. 2 an exemplary embodiment of the discompleteneural controller 100 applied to an isolated biceps muscle is presented,as described above, the discomplete neural controller 100 is alsoreferred to as a discomplete neural prosthesis. In this exemplaryembodiment an implanted neural prosthesis 200 is depicted. The implantedneural prosthesis 200 is used to measure a volitional electrical signal102 manifest in the biceps muscle 202 that would otherwise be clinicallyparalyzed because the nerves that innervate the muscle are below alesion in the nervous system that results in a discomplete neurallesion. In this embodiment the volitional electrical signal 102 ispicked up from the muscle via an epimysial electrode 204 that is affixedto the body of the biceps muscle 202. The epimysial electrode 204 isoperably connected to an input I₁ 206. The input I₁ 206 is in theembodiment depicted is incorporated in a controller module 208.

The implanted neural prosthesis 200 is implanted within the use's body,thereby allowing the operable connection between the epimysial electrode204 and the input I₁ 206 to be made via a conductive wire as known tothose of ordinary skill in the art. The input I₁ 206 is adapted tomeasure the volitional electrical signal 102 via the epimysial electrode204 as manifest in the body of the biceps muscle 202 by the user. Asknown to those of ordinary skill in the art, the input I₁ 206 in thisembodiment embodies an analog front end that is adapted to filter andamplify the volitional electrical signal 102 while minimizing any changeto the volitional electrical signal 102 due to the measurement itself.In one embodiment, the input I₁ 206 incorporates a bandpass filter withlower cutoff of about 10 Hz and higher cutoff of about 1 kHz. The inputI₁ 206 in the embodiment depicted further comprises an analog to digital(A/D) converter adapted to receive the volitional electrical signal 102and convert it into a digital representation thereof, the digitalvolitional signal 212.

In the embodiment depleted a secondary source of information is providedby a joint angle sensor 214 that is implanted in the elbow joint. Thejoint angle sensor 214 is operably connected to a sensor input S₁ 216that accepts the raw signal from the joint angle sensor 214, performsnecessary analog signal filtering, amplification and processing andconverts the joint angle sensor 214 signal to a digital joint anglesignal 218. The joint angle sensor 214 is one exemplary embodiment ofwhat is generally referred to as state measurement or state estimationsensors. These sensors are used to measure or estimate user states orenvironmental states or a combination thereof that are indicative of theuser's body state or configuration and the environment surrounding theuser.

The digital volitional signal 212 and the digital joint angle signal 218are in turn used by the controller 104 to estimate the command desiredby the user of the system. In the implanted neural prosthesis 200, thecontroller computer component 210 is adopted to receive the digitalvolitional signal 212 and the digital joint angle signal 218. Thecontroller computer component 210 is in this embodiment housed withinthe controller module 208.

The controller computer component 210 comprises two logical components,a command generation component 220 and an output control component 224.The command generation component 220 and the output control component224 in the embodiment depicted in FIG. 2 are both logical components ofthe controller computer component 210. As is appreciated by one ofordinary skill in the an the command generation component 220 and outputcontrol component 224 are capable of residing in physically distributedmodules that are located in different parts of the user and networkedtogether.

The command generation component 220 comprises an algorithm adapted toestimate the user's desired command based at least in part on thedigital volitional signal 212. In the embodiment depicted in FIG. 2, thecommand generation component 220 is adapted to receive both the digitalvolitional signal 212 and the joint angle signal 218. The commandgeneration component 220 generates a digital command signal 222 inresponse to the digital volitional signal 212 and the joint angle signal218. In one exemplary embodiment, the digital volitional signal 212 isused to as an on/off or signal. In this embodiment the volitionalelectrical potential 102 created by the user, and digitized by the inputI₁ 206 to create a digital volitional signal 212 is processed todetermine whether the user has exceeded a threshold value (i.e. alogical state change). Once the user exceeds the threshold value, thecommand generation component 220 interprets this as the riser requestinga change in logical state. In the embodiment depicted where the commandgeneration component 220 generated a command signal 222 based on bothdigital joint angle signal 218 well as the digital volitional signal212, the interpretation of the change in digital volitional signal 212across the logic threshold is adjusted according to the digital jointangle signal 218. In one exemplary embodiment, if the digital jointangle signal 218 is within a first range of angles, the change indigital volitional signal 212 indicating a logical state change isinterpreted to be a request to actuate an external device while the samelogical state change from the digital volitional signal 212 occurringwhen the digital joint angle signal 218 is in a different joint anglerange results in a command to actuate specific muscles to createfunctional movement.

The command generation component 220 is operably connected to the outputcontrol component 224 and the output control component 224 is adapted toreceive the command signal 222. The command signal 222 providesinstructions to the output control component 224 on the user's desiredcommands. The output control component 224 then maps the command signal222 onto controller module 208 outputs.

In the embodiment of the controller module 208 depicted in FIG. 2, twotypes of outputs are present. One output is a device output A₁ 226 thatis adapted to be coupled to an external device. In the embodimentdepicted m FIG. 2 the external device is a television remote control 228that is coupled to the device output A₁ 226 at least in part by anelectromagnetic signal. In the embodiment depicted in FIG. 2, where thecontroller module 208 is fully implanted, the external commandconnection 236 is at least partially wireless allowing a signal to passfrom inside the user's body to an external device. For example, theexternal command connection 236 in one embodiment is an inductivelycoupled link, in another embodiment is a short range, radio-frequencylink. The device output A₁ 226 is readily adapted by one of ordinaryskill in the art to actuate other external devices, such as activeorthotic devices, lights, or computer systems. The second output is tostimulator output O₁ 230. The stimulator output O₁ 230 is operablyconnected to the biceps muscle 202 via a stimulating electrode, in thisease an intramuscular electrode 234 and is adapted to generate stimuluspatterns that cause the biceps muscle 202 to contract.

The mapping component or output control component 224 determines andgenerates a control signal 232 to output the appropriate signals fromthe controller module 208 to achieve the use's desired functionalaction. For example, in the foregoing embodiment, the control signal 232applied to the device output A₁ 226 is a command to increment thechannel upwards or a specified level of muscle stimulation output viathe stimulator output O1 230 to the biceps muscle 202 via theintramuscular electrode 234. In another embodiment the output controlcomponent 224 maps the command signal 222 to the control signal 232 tobe applied to the biceps muscle 234 based on to stimulation map that iscreated using clinical procedures that map stimulation parameters ontocommand signals 222.

As appreciated by one of ordinary skill in the art, the discompleteneural controller 100 is readily adapted by one of ordinary skill in theart to control a combination of one or more muscles, and one or moreexternal devices using a combination of volitional electrical potential102 and other sensors such as joint angle sensors, gravity vectorsensors, force or pressure sensors.

In the embodiment depicted in FIG. 2, the volitional electricalpotential 102 created by the user either in the some muscle or musclethat is proximate to the that is stimulated via the intramuscularelectrode 234. In the embodiment of the implanted neural prosthesis 200depicted in FIG. 2, the myoelectric signal is the volitional electricalpotential 102 that is generated by the user. In other embodiments,combinations of voluntary myoelectric signals (i.e. generated by theuser above the lesion) are combined with one or more volitionalelectrical potentials 102 to provide signals or input to the commandgeneration component 220.

Generating Command Signals

As introduced in the exemplary embodiment of an implanted neuralprosthesis 200 described above, a command signal 222 is generated by thecommand generation component 220 based on inputs received by the commandgeneration component 220 front the user's volitional electricalpotential 102 (via Input I₁ 206) and other environmental informationfrom environmental and state sensors, such as the joint angle sensor 214via the sensor input S₁ 216. The command generation component 220 invarious embodiments outputs a variety of different command signal types.The command signal types include triggering signals (on/off or logicsignals and triggering of complex patterns), force or modulated levelinformation, and combinations of both. Thus the command generationcomponent 220 operates to intuit the desires of the user based on theuser's volitional electrical potential 102 and other information,including information about the user's environment, body state, andother inputs such as voice or other inputs that are not impacted by thediscomplete neural lesion. A description of these various command signaltypes is provided in relation to specific functional tasks.

Augmentation Control Mode

In an augmentation control mode the, discomplete neural controller 100operates to enhance the volitional commands that the user is otherwiseapplying to a muscle to create a functional movement. In another aspect,the discomplete neural controller 100 operates to activate nearbymuscles that have a functionally similar motion to the muscle where theuser is able to volitionally elicit recordable EMG activity.

For example, in the case of shank extension, the user may have theability to create a volitional electrical potential 102 in one head ofthe quadriceps muscle, but is unable to either contract that heart ofthe muscle in a functional manner or illicit volitional electricalpotential 102 in the other beads of the quadriceps. When operating toaugment the user's latent volitional commands, the discomplete neuralcontroller 100 measures the volitional electrical potential 102 createdby the user when the user attempts to extend the shank. The measuredvolitional electrical potential 102 is interpreted by the system as acommand to contract the quadriceps muscle, with specifies regardingcommanded force and output signal to the stimulated head(s) of thequadriceps dictated by the controller 104.

One exemplary operational mode for a discomplete neural controller 100,presented in view of the implanted neural prosthesis 200 embodiment, isa stimulus augmentation mode. In this mode the user generates avolitional electrical potential 102 in the muscle to be stimulated, inthe case of the embodiment depicted in FIG. 2, the biceps muscle 202. Asdescribed above, a digital volitional signal 212 is generated thatcorresponds to the volitional electrical potential 102 created by theuser. The command generation component 220 then processes the digitalvolitional signal 212 to estimate the force desired by the user. Theforce desired by the user as estimated by the controller 208 via thedigital volitional signal 212 is used to adjust the command signal 222accordingly. For example, in the stimulus augmentation mode, thecontroller 208 detects in increase in volitional electrical potential102 caused by the user attempting to move the functionally paralyzedlimb. The controller 208 uses the digital volitional signal 212 todetermine whether to increase the stimulus pulse applied to the bicepsmuscle 202 or decrease the stimulus pulse based on the digitalvolitional signal 212.

In another embodiment the biceps muscle 202 is mapped to define maximumand minimum stimulus parameters and sensitivity to changes in thestimulation pattern (i.e. adjustments to pulse width, interpulseinterval, pulse height etc.). The increase or decrease in the digitalvolitional signal 212 is also mapped to determine the maximum volitionalelectrical potential 102 the user is capable of generating. Then thecontroller 208 utilizes a proportional difference between the maximumand actual volitional electrical potential 102 and the mappedstimulation parameters to generate a command signal 222 for thestimulation pattern output to the biceps muscle 202 that is mappedproportionally to the volitional electrical potential 102 commanded bythe user.

Sample and Stimulate

Referring again to the embodiment of the implanted neural prosthesis 200depicted in FIG. 2, the measurement or sampling of the volitionalelectrical potential 102 in the presence of muscle stimulation isdetailed. There are multiple methods known to those of ordinary skill inthe art for sampling and stimulating on the same muscle or muscles thatare nearby where stimulation of the muscle causes saturation of themyoelectric signal on the unstimulated muscles.

For exemplary purposes, one system and method for obtaining volitionalelectrical potential 102 from a muscle in the presence of stimulationartifacts is described by referring to the sampling block diagramprovided of FIG. 3. A block diagram of a sampling circuit 300 adapted torecord myoelectric signals generally and more specifically volitionalelectrical potential 102 signals in the presence or stimulationartifacts is detailed. As appreciated by one of ordinary skill in theart, the sampling circuit 300 implemented in the implanted neuralprosthesis 200 embodiment of a discomplete neural controller 100incorporates the sampling circuit as part of the input I₁ 206. Thus theinput I₁ 206 is adapted to provide sampling around the stimulationoutput by the stimulator output O₁ 230 to the muscle via theintramuscular electrode 234. The sampling circuit 300 details thedifferential reference electrodes of the epimysial electrode 204 as apair of two differential EMG recording electrodes 302 and the referenceelectrode 344.

The volitional electrical potential 102 recorded by the EMG recordingelectrodes 302 and reference electrode 304 are input to thepre-amplifier component 306. The pre-amplifier component 306 in theembodiment depicted incorporates a differential amplifier 308 and abandpass filter 310. The bandpass filter 310 has in one embodiment a lowfrequency cut off of about 300 Hz and a high frequency cut off of about1000 Hz. In other embodiments the bandpass filter 310 cutoff frequenciesare selected by one of ordinary skill in the art to reduce 60 Hz noise,high-frequency signals from the hospital and medical environments andrecharge artifact created by the stimulation of the muscle. Thepre-amplified signal is then amplified via an amplifier 312 and thenrectified via a full-wave rectifier 314 before entering the sampling andfiltering circuit 316.

The sampling and filtering component 316 is comprised of a seriescascade of an analog switch 318, and integrator 320 a sample and holdcircuit 322 and an adaptive filter 324. A timing component 326 is usedto select the portion of the volitional electrical potential 102 signalpresent between stimulating pulses. In one exemplary embodiment whenstimulating pulses are delivered with a minimum of about 45 ms betweenstimulation bursts, the timing component 326 is used to sample thevolitional electrical potential 102 only during the last about 35 msbetween the stimulating pulses. The integrator 320 is reset betweensstimulating pulses by the same timing component 326. The signal outputfrom the integrator 320 is output to a sample and hold circuit 322 thatin turn is connected to the adaptive filter 324.

In the embodiment depicted two separate adaptive filter 324 embodimentsare used. In one embodiment an adaptive time constant filter with afirst order low pass filter where the time constant is varies as afunction of the derivative of a fixed time constant parallel filter. Theparallel filter in one aspect is a second order Butterworth filter witha time constant of 250 ms that allowed the time constants of theadaptive filter to range between 60 ms to 1.2 ms. The output of theadaptive filter 324 is an analog command signal 326 that corresponds tothe volitional electrical potential 102 measured between musclestimulating pulses. The volitional signal 326 is sampled via ananalog-to-digital converters 330 to generate the digital volitionalsignal 212 that is used the command controller module 208 to generatethe command signal 222 which in turn is used by the timing component 326to coordinate sampling.

In the second embodiment an adaptive step-size or slew rate limitingfilter is used for the adaptive filter 324. In this second embodiment,each time the stimulus command to the muscle is updated, a comparison ismade between the current command signal 222 and the command signal 222during the previous stimulation update. The allowable step size (slewrate) is started at a minimum value and the actual command is movedtoward the desired command by no more than the allowable step size. Witheach successive step size in the same direction (i.e. increase ordecrease the command signal 222) the stepsize is increased exponentiallyup to the maximum step size. Each time the step direction changes, thestep size is reset to the minimum value.

As appreciated by one of ordinary skill in the art, in alternativeembodiments of the discomplete neural controller 100 the volitionalelectrical potential 102 is obtained from non-involved muscles or nerveswhere stimulation related artifacts are either significantly attenuatedor are undetectable. Thus in alternative embodiments the volitionalelectrical potential 102 sampling process is not required.

Triggering

In another control mode of the discomplete neural controller 100, thevolitional electrical potential 102 is used by the controller 104 as alogical control input. A logical control, or triggering commandresembles a digital logic or on/off signal. In the ease of a volitionalelectrical potential 102, the on/off signal is tailored to change stateupon the user applying the volitional electrical potential 102.

The volitional electrical potential 102 used for triggering isprocessed, which in the case of a volitional electrical potential 102not impacted by stimulus artifacts (i.e. no stimulus is output such aswhere the controller is used to only control an external plant 108 andnot simulate muscle or where the stimulated muscle are isolated from themeasured volitional electrical potential 102). In these embodiments,rather then using the sampling circuit 300 described above traditionalanalog filtering and amplification is used to amplify and remove noisefrom the volitional electrical potential 102. The signal characteristicsof the volitional electrical potential 102 is then used by thecontroller 104 to determine if the user has created a large enoughvolitional electrical potential 102 to cause the state of that channelto switch from the baseline or no potential to the complimentary state(i.e. from on to off or visa versa).

The volitional electrical potential 102 is evaluated by the controller104 using a variety of means to estimate the signal characteristics. Oneor more signal characteristics of a volitional electrical potential 102are suitable for mapping into a measureable signal. In fact, differentvolitional electrical potentials 102 collected different muscles ornerves may have different characteristics due to the number and qualityof axons that actually cross the lesion. In one embodiment, the totalenergy of the volitional electrical potential 102 is calculated byintegrating either the rectified signal or the signal squared over afixed period of time. In another embodiment, a windowed Fouriertransform, or digitally implemented fast Fourier transform (FFT) is usedto estimate both frequency characteristics as well as signal energyduring the fixed interval. In yet another embodiment a time-frequencyanalysis or wavelet analysis is used to gather the time-varyingcharacteristics of the volitional electrical potential 102. In one modethe user is required to hold a volitional electrical potential 102greater than a threshold value for multiple sampling windows in order tocase the controller 104 to identify a trigger command. In the aboveanalysis techniques a baseline volitional electrical potential 102mapping is used to calibrate the discomplete neural controller 100.

The initial mapping process for identifying muscles and nerves where auser is capable of generating measurable, but still sub-functional,volitional electrical potential 102 is an initial starting point fortailoring the discomplete neural controller 100 far a variety of users.Specifically, one of the initial steps to the process is identifyingwhich muscles and nerves of the user are still controlled by the userand capable of generating volitional electrical signals 102. Thisinitial screening in one embodiment is performed pre-operatively usingsurface EMG recording electrodes or percutaneous needle electrodes tomeasure volitional electrical signals 102 generated by the user. In thismanner muscles and nerves that are still partially under the volitionalcontrol of the user are identified and the amount of force and othercharacteristics of the user's volitional electrical potential 102 areinitially characterized. After identification of candidate muscles andnerves, systems with implanted electrodes are implanted and the user'svolitional electrical potential 102 is again characterized. After thecompletion of this characterization process it is possible to createmapping functions that allow the controller 104 to identify andcharacterize a user's volitional electrical potential 102.

The characterization, process for the user's volitional electricalpotential 102 is initiated by having the user attempt to ‘move’ aparticular paralyzed limb or muscle. The discomplete neural lesionresults in no clinical movement of the limb, however the user maygenerate a volitional electrical potential 102. The resulting volitionalelectrical potential 102 is initially characterized based on having theuser attempt to move the limb or generate a desired force level. In oneembodiment the user is simply asked to generate maximal force. In otherembodiments, the user is presented a real-time feedback of thevolitional electrical potential 102 levels allowing the user to attemptto control to desired marks. During the characterization process, thevolitional electrical potential 102 is recorded and characterized toestimate the total force the user is able to generate and assess theability of the user to generated graduated or various levels of control.The characterization information is used to customize a particularcontroller 104 and mote specifically a command generation component 220to a given user's ability to generate volitional electrical potential102 in muscles and nerves based on the type of actuation available tothe user.

Referring again to the case of a triggering input, the triggering inputdetermines whether or not to switch the state or the command signal froman initial state to a second state. In one embodiment, the initial stateis a default state of the toggle switch (e.g. 0) corresponds to abaseline or no volitional electrical potential 102 generated by the userwhile the complimentary state (e.g. 1) corresponds to an elevated levelof volitional electrical potential 102, thus when the volitionalelectrical potential 102 returns to baseline or zero level the toggleswitches back to the default state (e.g. 0). In another embodiment, thetriggering input causes only a state change from its current state tothe next state (i.e. in the ease of a binary switch toggling to theother state—e.g. from a 1 to a 0 or visa versa).

In embodiments with multiple state switches, when the volitionalelectrical potential 102 exceeds the trigger state the switch stateincrements by a fixed amount (i.e. moving from the current mode toanother mode). For example, in one aspect the switch state may possessthree separate modes of operation, a first state corresponding to nostimulus, a second state corresponding to a specific grasp pattern (e.g.palmar grasp) or other action applied to the plant 108, and third statecorresponding to a second grasp pattern (e.g. lateral grasp) or otheraction applied to the plant 108.

In other embodiments, multiple inputs are used by the controller 104 todetermine the user's desired action. In one exemplary embodiment, afirst volitional electrical potential 102 signal is used as a toggleinput, where the action of the first volitional electrical potential 102signal is used to toggle the state of the controller 104 from mode tomode, such as the exemplary grasp mode controller described in thepreceding paragraph. Then a second volitional electrical potential 102signal is used by the controller to adjust the force desired for thegrasp. In this embodiment, each discrete pulse by the user of the secondvolitional electrical potential 102 would cause the controller 104 tointerpret the user as requesting the force to be increments from thecurrent force level to the next force level. One of ordinary skill inthe art can adapt the forgoing exemplary embodiment to scenarios withmultiple volitional electrical potential 102 signals or other EMG orexternal input devices (e.g. joysticks, buttons, voice input, etc.).

Sequence Triggering

In another exemplary embodiment, the controller 104 utilizes thevolitional electrical potential 102 created by the user, in some casesin conjunction with other inputs such as EMG signals or input devices toselect, initiate and modulate pre-defined sequences of commands. Forexample, in an embodiment of the discomplete neural controller 100applied to functional walking, the user may first select and walkingmode for the controller 104. In the walking mode, the controller 104 isinterpreting volitional electrical potential 102 signals as beingindicative of the use's desired action (e.g. lifting a leg, stopping thegait cycle, transfer of weight, etc). Thus, when the volitionalelectrical potential 102 signal or signals from volitional electricalpotential 102 are received the controller 104 interprets the volitionalelectrical potential 102 as being indicative of the user requesting thenext step in the sequence or modulating the sequence. In one example,for a walking mode of the discomplete neural controller 100 used forlower extremity functional motion, the volitional electrical potential102 signal from the user is interpreted by the discomplete neuralcontroller 100 to initiate the next sequence of commands for lifting aleg. Thus an entire series of command signals 222 are initiated by avolitional electrical potential 102 from the user.

Estimation of User Commands

The discomplete neural controller 100 uses at least in part volitionalelectrical potential 102 information to estimate the use's desiredcommands. As described in relation to the embodiment of an implantedneural prosthesis 200, a command generation component 220 accepts themeasured volitional electrical potential 102 generated by the user andmeasured by the input I₁ 206 to the controller module 208 (i.e. thedigital volitional signal 212) as part of its input. The commandgeneration component 220 also accepts in other embodiments inputs suchas state measurement information from sensors in the user or other useractuated information (including signals from other parts of the use'sburly above the lesion) as well as information or knowledge of thecontroller's 104 internal state and control output 106 slate to estimatethe user's desired commands. The user's estimated or desired commandsare then output as a command signal 222 to the output control component224 that outputs the necessary signals to the stimulation electrodes orother external actuators to achieve the desired result. As is readilyappreciated by those of ordinary skill in the art, the commandgeneration component 220 is frequently tailored to the specific trainingand capabilities of the user and over time the command generationcomponent 220 may be adapted either automatically or manually to adjustthe resulting command signal 222.

The command generation component 220 is implemented in the controller104 to estimate the user's desired command. In one embodiment thecommand generation component 220 uses a rule-base, heuristic or expertsystem based approach to interpret the inputs to the command generationcomponent 220 and estimate the user's desired commands and output thatas a command signal 222 adapted for input to the output controlcomponent 224. In another embodiment a fuzzy logic system is used toclassify the inputs and output a command signal 222. In still anotherembodiment a form of neural network is trained to classify the inputsand output a command signal 222 that reflects the use's desired goals.In other embodiments, combinations of the foregoing are combined andadapted to operate together in order to properly classify the user'sdesired commands and generate a command signal 222.

The command signal 222 is then accepted by the output control component224 which in turn generates specific output commands for the stimulatedmuscles and other devices attached or controlled by the discompleteneural controller 100. In one embodiment the output control component224 uses an inverse map generated from the user's response, to stimuluscommands to generate the control signal 232 output via the stimulatoroutput O₁ 230. In another embodiment a neural network is trained andused to generate the control signal 232 based on the command signal 222.In still other embodiments, heuristic, rules-based, expert systems orfuzzy logic is used by the output control component 224 to generate thecontrol signal 232. In still other aspects, combinations of theforegoing are used by the output control component 224 to generate thecontrol signal 232. In still other embodiments, the control signal 232is further modulated by state information provided by other sensors thatmeasure both internal body states as well as external environment stateinformation.

Exemplary Implementation—Partially Implanted System

Referring now to FIG. 4, an embodiment of the discomplete neuralcontroller 100 is depicted as a partially implanted upper extremityprosthesis 400. The partially implanted upper extremity prosthesis 400depicted uses multiple stimulating electrodes 402 that are operablelyconnected to an implanted recording stimulator 412. The implantedrecording stimulator 410 is adapted to both receive inputs from eithermyoelectric or electrical potentials manifest in peripheral nerves. Theimplanted recording stimulator 410 is connected via an inductive link toan external control unit 414 that is worn on the user's belt. Theinductive link in the embodiment depicted is provided via an pair ofinductive coils 412 that are operably connected to at one end to theimplanted recording stimulator 410 and the external control unit 414 toenable the external control unit 414 to both provide power andcommunicate with the implanted recording stimulator 412.

The partially implanted upper extremity prosthesis 400 depicted in FIG.4 includes three separate inputs from the user to provide commandinformation to the controller 104. The first is a recording electrode404 adapted to record a first volitional electrical potential 102generated by the user on or in proximity to one of the muscles beingstimulated by a stimulating electrode 402. As discussed above, therecording electrode 404 input to the implanted recording stimulator 410is sampled in order to capture volitional electrical potential 102signals while avoiding stimulation artifacts from the electricalstimulation delivered via the stimulating electrodes 402. A second,uninvolved recording electrode 406 is placed in an isolated locationwhere the volitional electrical potential 102 is relatively isolatedfrom the stimulating pulses.

The partially implanted upper extremity prosthesis 400 also includes animplanted switch 408. The implanted switch 408 is placed in a locationwhere the user can actuate the switch using their muscle control byadjusting their shoulders.

The implanted recording stimulator 410 receives the information from therecording electrode 402, uninvolved recording electrode 406 andimplanted switch 408. The combination of volitional electrical potential102 signals and the switch information is initially processed andprovided to the external control unit 414 in this embodiment as usergenerated signals. The external control unit 414 processes theinformation to estimate the user's desired command that is then turnedinto control outputs 106 that are passed to the implanted recordingstimulator 410 to be issued as stimulus commands to the muscles via thestimulating electrodes 402. As discussed previously, external devicessuch as a remote lamp or orthotic device are also readily adapted foractuation by the external control unit 414.

As discussed above the external control unit 414 may use multiplecombinations of different logic functions to estimate the user's desiredcommand. For example, as discussed above with respect to the embodimentthe implanted neural prosthesis the user generated signals are processedby the command generation component 220 to estimate the user's desiredcommands represented as a command signal 222. Thus, in the embodimentdepicted a combination of user inputs that include volitional electricalpotential 102 signals and other inputs are used by the commandgeneration component 220 to determine the control output 106. In theembodiment depicted, the input signal from the volitional electricalpotential 102 is recorded via the implanted recording stimulator 210.Thus the recording stimulator 210 pre-filters, amplifies and digitizesthe volitional electrical potential 102 signals from the recordingelectrode 402 and the uninvolved recording electrode. The resultingsignal is passed to the external control unit 414 where the commandgeneration component 220 resides. In other embodiments, a person ofordinary skill in the art may readily distribute some or all of thefunctional elements of the command generation component 220 to theimplanted recording stimulator 410 in addition to or in lieu of theexternal control unit 414.

Exemplary Implementation—External System

Referring now to FIG. 5, another exemplary embodiment of a discompleteneural controller 100 is illustrated, in this embodiment an externalneural prosthesis 500 is shown. In this embodiment, an externalrecording electrode 502 is affixed to the surface of the user's leg torecord volitional electrical potential 102 signals. In an alternativeembodiment not shown, a percutaneous or needle electrode is used tofurther isolate the volitional electrical potential 102 to a specificmuscle and increase sensitivity. The volitional electrical potential 102is measured by an external controller 506 that receives the volitionalelectrical potential 102 from the external recording electrode 502. Theexternal controller 506 in this embodiment includes both a commandgeneration component 220 as well as an output control component 224. Thevolitional electrical potential 102 signals and other signals providedby other inputs and sensors (not shown in FIG. 5), such as gravitysensors, heel strike sensors, or instrumented orthotic braces etc. arealso input to the external controller 506. The external controller 506and more specifically the command generation component 220 of theexternal controller 506 (not shown in FIG. 5) estimates the user'sdesired action based on these volitional electrical potential 102signals and other inputs. The external controller 506 then uses thecommand signal 222, estimated by the command generation component 230,to the output control component 224 (also not shown in FIG. 5). Theresulting control signal is output by the external controller 506 toactive an external stimulating electrode 504, in this embodiment asurface electrode. The resulting control signal is also output by theexternal controller 506 in this embodiment via a wireless signalinterface to an remote device 508, in this case a lamp.

Exemplary Electrical Potential

Referring now to FIG. 6, a plot 600 demonstrating experimental resultsof a user creating volitional electrical potential 102 signals with aclinically complete lesion caused by an SCI is shown. The plot 600comprises a reference signal 602 that shows an external prompt providedto the user requesting that the user to generate a volitional electricalpotential 102 associated with a paralyzed muscle. The volitionalelectrical potential 102 is collected with an external recordingelectrode 504 configured to receive volitional electrical potential 102generated by the user. The plot 600 demonstrates the ability of the userto generate a volitional electrical potential 102 on demand, which inturn is used by the discomplete neural controllers 100 of the presentsystem and method to apply control signals to a plant.

Conclusion

While various embodiments of the present system and method for controlusing electrical signals obtained from functional paralyzed muscles andnerves are described above, it should be understood that the embodimentshave been presented by the way of example only, and not limitation. Itwill be understood by those skilled in the art that various changes inform and details may be made therein without departing from the spiritand scope of the invention as defined. Thus, the breadth and scope ofthe present invention should not be limited by any of the abovedescribed exemplary embodiments.

1-21. (canceled)
 22. A neural prosthesis system, comprising: anelectrode configured to detect a volitional electrical potentialgenerated within a human body below a lesion in the nervous system; anda controller coupled to the electrode and configured to generate acontrol signal that causes a plant to respond in a functional mannerbased on the detected volitional electrical potential.
 23. The neuralprosthesis system of claim 22, wherein the control signal is configuredto cause the plant to make a functional movement.
 24. The neuralprosthesis system of claim 23, wherein the controller is configured togenerate the control signal to cause the functional movement of theplant based on the volitional electrical potential.
 25. The neuralprosthesis system of claim 22, wherein the controller is furtherconfigured to generate the control signal based on a state of the humanbody and the detected volitional electrical potential.
 26. The neuralprosthesis system of claim 22, controller is configured to generate thecontrol signal based on an inverse map of the plant.
 27. The neuralprosthesis system of claim 22, wherein the electrode is configured todetect the electrical potential generated by a muscle within the humanbody below the lesion in the nervous system; and wherein the plantcomprises the muscle within the human body.
 28. The neural prosthesissystem of claim 22, wherein the electrode is configured to detect theelectrical potential generated by a peripheral nerve within the humanbody below the lesion in the nervous system; and wherein the plantcomprises a muscle within the human body innervated by the nerve. 29.The neural prosthesis system of claim 22, wherein the controller isconfigured to modulate the control signal based on the detectedvolitional potential.
 30. The neural prosthesis system of claim 22,wherein the controller is configured to estimate a total energy of thedetected volitional potential and modulate the control signal based onthe total energy.
 31. The neural prosthesis system of claim 22, whereinthe controller is further configured to output the control signal to theplant.
 32. A method for neural control, comprising: receiving a signalin response to detection of a volitional electrical potential generatedwithin a human body below a lesion in the nervous system; generating acontrol signal based on the detected volitional electrical potential,wherein the control signal is configured to cause a plant to respond ina functional manner; and applying the control signal to the plant. 33.The method of claim 32, wherein the human body is clinically paralyzedbelow the lesion in the nervous system.
 34. The method of claim 32,further comprising detecting the volitional electrical potentialgenerated by at least one of a nerve and a muscle below the lesion inthe nervous system.
 35. The method of claim 34, wherein the detectedvolitional potential corresponds to a desired functional response of theplant.
 36. The method of claim 34, wherein the plant comprises themuscle; and wherein the muscle is unable to contract based on thevolitional electrical potential.
 37. A controller device, comprising: aninput configured to receive an input signal based on a detectedelectrical potential, wherein the electrical potential is generated by ahuman body below a lesion in the nervous system; a generator configuredto generate a control signal in response to the input signal based onthe detected electrical potential; and an output configured to apply thecontrol signal to a plant to cause the plant to respond in a functionalmanner.
 38. The controller device of claim 37, wherein the generator isfurther configured to alter the control signal based on a state of thehuman body.
 39. The controller device of claim 37, wherein the generatoris further to generate a second control signal in response to a secondinput signal corresponding a second detected electrical potential;wherein the second control signal causes the plant to respond in asecond functional manner.
 40. The controller device of claim 37, whereinthe plant comprises a paralyzed muscle below the lesion in the humanbody.
 41. The controller device of claim 37, wherein the electricalpotential is generated by a nerve or a muscle below the lesion in thenervous system.